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Make binary bin search reusable. (#6058)

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* Move binary search row to hist util.
* Remove dead code.
This commit is contained in:
Jiaming Yuan
2020-08-26 05:05:11 +08:00
committed by GitHub
parent 9c14e430af
commit 80c8547147
8 changed files with 56 additions and 102 deletions
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10
src/tree/gpu_hist/histogram.cu
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@@ -34,7 +34,7 @@ namespace tree {
* to avoid outliers, as the full reduction is reproducible on GPU with reduction tree.
*/
template <typename T>
DEV_INLINE __host__ T CreateRoundingFactor(T max_abs, int n) {
XGBOOST_DEV_INLINE __host__ T CreateRoundingFactor(T max_abs, int n) {
T delta = max_abs / (static_cast<T>(1.0) - 2 * n * std::numeric_limits<T>::epsilon());
// Calculate ceil(log_2(delta)).
@@ -53,20 +53,20 @@ struct Pair {
GradientPair first;
GradientPair second;
};
DEV_INLINE Pair operator+(Pair const& lhs, Pair const& rhs) {
XGBOOST_DEV_INLINE Pair operator+(Pair const& lhs, Pair const& rhs) {
return {lhs.first + rhs.first, lhs.second + rhs.second};
}
} // anonymous namespace
struct Clip : public thrust::unary_function<GradientPair, Pair> {
static DEV_INLINE float Pclip(float v) {
static XGBOOST_DEV_INLINE float Pclip(float v) {
return v > 0 ? v : 0;
}
static DEV_INLINE float Nclip(float v) {
static XGBOOST_DEV_INLINE float Nclip(float v) {
return v < 0 ? abs(v) : 0;
}
DEV_INLINE Pair operator()(GradientPair x) const {
XGBOOST_DEV_INLINE Pair operator()(GradientPair x) const {
auto pg = Pclip(x.GetGrad());
auto ph = Pclip(x.GetHess());

2
src/tree/gpu_hist/histogram.cuh
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@@ -16,7 +16,7 @@ template <typename GradientSumT>
GradientSumT CreateRoundingFactor(common::Span<GradientPair const> gpair);
template <typename T>
DEV_INLINE T TruncateWithRoundingFactor(T const rounding_factor, float const x) {
XGBOOST_DEV_INLINE T TruncateWithRoundingFactor(T const rounding_factor, float const x) {
return (rounding_factor + static_cast<T>(x)) - rounding_factor;
}

52
src/tree/updater_gpu_common.cuh
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@@ -114,58 +114,6 @@ struct DeviceSplitCandidateReduceOp {
}
};
struct DeviceNodeStats {
GradientPair sum_gradients;
float root_gain {-FLT_MAX};
float weight {-FLT_MAX};
/** default direction for missing values */
DefaultDirection dir {kLeftDir};
/** threshold value for comparison */
float fvalue {0.0f};
GradientPair left_sum;
GradientPair right_sum;
/** \brief The feature index. */
int fidx{kUnusedNode};
/** node id (used as key for reduce/scan) */
NodeIdT idx{kUnusedNode};
XGBOOST_DEVICE DeviceNodeStats() {} // NOLINT
template <typename ParamT>
HOST_DEV_INLINE DeviceNodeStats(GradientPair sum_gradients, NodeIdT nidx,
const ParamT& param)
: sum_gradients(sum_gradients),
idx(nidx) {
this->root_gain =
CalcGain(param, sum_gradients.GetGrad(), sum_gradients.GetHess());
this->weight =
CalcWeight(param, sum_gradients.GetGrad(), sum_gradients.GetHess());
}
HOST_DEV_INLINE void SetSplit(float fvalue, int fidx, DefaultDirection dir,
GradientPair left_sum, GradientPair right_sum) {
this->fvalue = fvalue;
this->fidx = fidx;
this->dir = dir;
this->left_sum = left_sum;
this->right_sum = right_sum;
}
HOST_DEV_INLINE void SetSplit(const DeviceSplitCandidate& split) {
this->SetSplit(split.fvalue, split.findex, split.dir, split.left_sum,
split.right_sum);
}
/** Tells whether this node is part of the decision tree */
HOST_DEV_INLINE bool IsUnused() const { return (idx == kUnusedNode); }
/** Tells whether this node is a leaf of the decision tree */
HOST_DEV_INLINE bool IsLeaf() const {
return (!IsUnused() && (fidx == kUnusedNode));
}
};
template <typename T>
struct SumCallbackOp {
// Running prefix